Automatic Contrast Enhancement Using Reversible Data Hiding with Distortion Minimization

Suah Kim, Hyoung Joong Kim

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Automatic contrast enhancement using reversible data hiding (ACERDH) has been found to be useful in automatic image enhancement field. Instead of just providing data hiding ability, ACERDH also equalizes the pixel histogram as a part of data hiding process. This allows original image recovery directly from the enhanced image, without any additional data, which provides file saving feature by not having to save the original image. In this paper, we propose two improvements and two novel distortion minimization methods for ACERDH [1] method. The experimental results show that the proposed method has higher embedding capacity and lower distortion than ACERDH.

Original languageEnglish
Title of host publication2019 IEEE 4th International Conference on Image, Vision and Computing, ICIVC 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages291-295
Number of pages5
ISBN (Electronic)9781728123257
DOIs
Publication statusPublished - 2019 Jul
Event4th IEEE International Conference on Image, Vision and Computing, ICIVC 2019 - Xiamen, China
Duration: 2019 Jul 52019 Jul 7

Publication series

Name2019 IEEE 4th International Conference on Image, Vision and Computing, ICIVC 2019

Conference

Conference4th IEEE International Conference on Image, Vision and Computing, ICIVC 2019
CountryChina
CityXiamen
Period19/7/519/7/7

Keywords

  • automatic contrast enhancement
  • reversible data hiding

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Vision and Pattern Recognition
  • Signal Processing
  • Media Technology

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  • Cite this

    Kim, S., & Kim, H. J. (2019). Automatic Contrast Enhancement Using Reversible Data Hiding with Distortion Minimization. In 2019 IEEE 4th International Conference on Image, Vision and Computing, ICIVC 2019 (pp. 291-295). [8980970] (2019 IEEE 4th International Conference on Image, Vision and Computing, ICIVC 2019). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICIVC47709.2019.8980970